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Feedbackyard - Audience Feedback and Interaction Toolkit
Feedbackyard - Audience Feedback and Interaction Toolkit
Audience will scan a QR code and provide feedback. That is it. You can check the product demo at: http://blog.feedbackyard.com/2013/08/we-are-building-abcdef-of-communication.html Expecting some feedback from the HN community.
Share cardActual performance
4points
2comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
34%34% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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